Customized multi-period stochastic assignment problem for social engagement and opportunistic IoT

An enormous number of devices are currently available to collect data. One of the main applications of these devices is in the urban environment, where they can collect data useful for improving the operations management and reducing economic, environmental and social costs. This is the main goal of smart cities. To gather these data from devices, companies can build expensive networks able of reaching every part of the city or they can use cheaper alternatives as opportunistic connections, i.e., use the devices of selected people (e.g., mobile users) as mobile hotspots in exchange for a reward. In this paper, we consider this second choice and, in particular, we solve the problem of minimizing the sum of the rewards while providing the connectivity to all sensors. We show that the stochastic approach must be considered since deterministic solutions produce considerable waste. Finally, to reduce the computational time we apply the loss of reduced costs-based variable fixing (LRCVF) heuristic and we compare, by means of computational tests, the performances of the heuristic and a commercial solver. The results prove the effectiveness of the LRCVF heuristic.